The DOI matches its Crossref record; 42 of the 43 references it cites were found in a registry or an index.
BCI Demographics: How Many (and What Kinds of) People Can Use an SSVEP BCI?
Abstract
Brain-computer interface (BCI) systems enable communication without movement. It is unclear why some BCI approaches or parameters are less effective with some users. This study elucidates BCI demographics by exploring correlations among BCI performance, personal preferences, and different subject factors such as age or gender. Results showed that most people, despite having no prior BCI experience, could use the Bremen SSVEP BCI system in a very noisy field setting. Performance tended to be better in both young and female subjects. Most subjects stated that they did not consider the flickering stimuli annoying and would use or recommend this BCI system. These and other demographic analyses may help identify the best BCI for each user.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As a result, the general concerns about the non-universal usability, robustness, and, especially, the role of training raised by able-bodied user studies [3–7] are even more pressing with regard to end-user populations.”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [7]
Citations
Cites
Brain–computer interfaces for communication and control
Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00057-3 · Cited by 7,927
The ten-twenty electrode system of the international federation
Jasper, H. H. (1958) · Electroencephalography and Clinical Neurophysiology · Cited by 6,567
A spelling device for the paralysed
Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler, A., Perelmouter, J., Taub, E., & Flor, H. (1999) · Nature · doi:10.1038/18581 · Cited by 1,577
Human Brain Electrophysiology: Evoked Potentials and Evoked Magnetic Fields in Science and Medicine
Regan, D. M. (1989) · Medical Entomology and Zoology · Cited by 1,300
Design and implementation of a brain-computer interface with high transfer rates
Cheng, M. J., Gao, X., Gao, S., & Xu, D. (2002) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2002.803536 · Cited by 820
Brain–computer interfaces: communication and restoration of movement in paralysis
Birbaumer, N., & Cohen, L. G. (2007) · The Journal of Physiology · doi:10.1113/jphysiol.2006.125633 · Cited by 763
Neuper, C., Scherer, R., Reiner, M., & Pfurtscheller, G. (2005) · Cognitive Brain Research · doi:10.1016/j.cogbrainres.2005.08.014 · Cited by 748
A P300-based brain–computer interface: Initial tests by ALS patients
Sellers, E. W., & Donchin, E. (2006) · Clinical Neurophysiology · doi:10.1016/j.clinph.2005.06.027 · Cited by 726
How many people are able to control a P300-based brain-computer interface (BCI)?
Guger, C., Daban, S., Sellers, E., Holzner, C., Krausz, G., Carabalona, R., Gramatica, F., & Edlinger, G. (2009) · Neuroscience Letters · doi:10.1016/j.neulet.2009.06.045 · Cited by 652
A practical VEP-based brain-computer interface
Wang, Y., Wang, R., Gao, X., Hong, B., & Gao, S. (2006) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2006.875576 · Cited by 622
Research works printed but not linked: 3
- valbuena, 2008, spelling with the bremen brain-computer interface and the integrated ssvep stimulator, Proc 4th Int Brain-Computer Interface Workshop Training Course, 291
- birbaumer, 0, Non-Invasive and Invasive Brain-Computer Interfaces
- allison, 0, Brain-Computer Interfaces Revolutionizing Human-Computer Interaction
Cited by
Sorted by citations
Items 301–343 of 343
Online implementation of top-down SSVEP-BMI
Ahn, M.-H., & Min, B. (2017) · International Winter Conference on Brain-Computer Interface (BCI) · doi:10.1109/iww-bci.2017.7858149 · Cited by 1
The Influence of the Modulation Index on Frequency-Modulated Steady-State Visual Evoked Potentials
Dreyer, A. M., Heikkinen, B. L. A., & Herrmann, C. S. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.859519 · Cited by 1
The Feasibility of EEG Based Multifactor Authentication
Khorkheli, L., Abraham, S., Chakravarty, V., Inocencio, S. A. M., & El-Messiry, H. (2024) · International Conference on Sustainable Mobility Applications, Renewables and Technology (SMART) · doi:10.1109/smart63170.2024.10815371 · Cited by 1
Convolutional neural networks decode finger movements in motor sequence learning from MEG data
Zabolotniy, A., Chan, R. W., Moiseeva, V., & Fedele, T. (2025) · Frontiers in Neuroscience · doi:10.3389/fnins.2025.1623380 · Cited by 1
Zhang, Y., Zhou, G., Jin, J., Wang, X., & Cichocki, A. S. (2013) · Cited by 1
How to identify the user specific stimulation frequencies for SSVEP-based BCI
Rejer, I., & Cieszyński, Ł. (2016) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2016.7844655 · Cited by 1
SSVEP-based BCI performance in children
Mullins, J. (2015) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 1
Hybrid Control and Game Design for BCI-integrated Action FPS Game
Tengtrakul, S., & Pan-ngum, S. (2020) · Advances in Computer-Human Interaction · Cited by 1
Bittencourt-Villalpando, M. (2018) · doi:10.11606/d.3.2018.tde-19032018-090128 · Cited by 1
Grigoryan, R., Goranskaya, D., Demchinsky, A., Ryabova, K., Kuleshov, D., & Kaplan, A. (2021) · Research Square · doi:10.21203/rs.3.rs-380982/v1 · Cited by 1
Orhan, U. (2013) · Digital Repository Service (Northeastern University) · doi:10.17760/d20004866 · Cited by 1
Steady state visual evoked potentials-based patient interface under breathing constraints
Navarro‐Sune, X., Campion, S., Fallani, F. D. V., Pouget, P., Similowski, T., Raux, M., & Chávez, M. (2015) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2015.7146579
Cao, T. F., Wong, C. M., Wan, F., & Hu, Y. S. (2014) · Advances in cognitive neurodynamics · doi:10.1007/978-94-017-9548-7_21
Bayesian Sequential Learning for EEG-Based BCI Classification Problems
Shigezumi, S., Hara, H., Namba, H., Serizawa, C., Dobashi, Y., Takemoto, A., Nakamura, K., & Matsumoto, T. (2013) · InTech eBooks · doi:10.5772/56146
Affective SSVEP BCI to effectively control 3D objects by using a prism array-based display
Mun, S., & Park, M. (2014) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2053651
ONLINE BRAIN-MACHINE INTERFACE WITH AUTOMATIC DETERMINATION OF STOPPING TIME OF TRAINING PHASE
Dobashi, Y., Takemoto, A., Shigezumi, S., Shiraki, T., Nakamura, K., & Matsumoto, T. (2012) · International Journal of Computational Bioscience · doi:10.2316/j.2012.210-1047
Chances for and Limitations of Brain-Computer Interface use in Elderly People
Mikołajewska, E., Mikołajewski, D., Komendziński, T., Dreszer, J., Lewandowska, M., & Wolak, T. P. (2014) · Advances in bioinformatics and biomedical engineering book series · doi:10.4018/978-1-4666-6094-6.ch007
Neuroscience, with a Specialization in Computational Neuroscience
Koerner, A. S. (2013)
Navigation In a Virtual Environment using Multi-class Motor Imagery Brain-Computer Interface
Chin, Z. Y., Ang, K. K., Guan, C., & Wang, C. (2013)
A Neurofeedback-Based Near-Infrared Spectroscopy Brain-Computer Interface
Weyand, S. (2015) · TSpace (University of Toronto)
Fundamentals: From Light to Command
Cotrina, A. (2017) · Human-computer interaction series · doi:10.1007/978-3-319-52298-2_2
Brain-Computer Interface in Intelligent Environment
Piróg, P. (2021) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-72254-8_22
Towards Context-aware Brain-computer Interfaces
Myrden, A. (2016) · TSpace (University of Toronto)
Assistance Robotics and Biosensors
Torres, F., Úbeda, A., & Puente, S. T. (2018) · MDPI eBooks · doi:10.3390/books978-3-03897-395-9
(2019) · IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) · doi:10.1109/civemsa45640.2019.9071622
Chances for and Limitations of Brain-Computer Interface use in Elderly People
Mikołajewska, E., Mikołajewski, D., Komendziński, T., Dreszer, J., Lewandowska, M., & Wolak, T. P. (2015) · IGI Global eBooks · doi:10.4018/978-1-4666-8789-9.ch084
Müller, K. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734961664.793562918
Between Digital Transformation and Cultural Evolution
Mekrami‐Guggenheim, I. (2022) · doi:10.1002/9781394163908.ch2
Active Feedback using Riemannian Features for Motor Imagery Classification
Gupta, V., Mittal, R., Ameta, D., Behera, L., & Sandhan, T. (2023) · International Conference on Bio Signals, Images, and Instrumentation (ICBSII) · doi:10.1109/icbsii58188.2023.10181030
Jeong, S., Chae, M. S., Kim, Y., Park, S., Ha, J., Bae, D., Cheon, S., & Mun, S. (2023) · Journal of Broadcast Engineering · doi:10.5909/jbe.2023.28.5.589
Padilla, G. L., Cano, L. A., Lucianna, F. A., Freire, E. O., Tagashira, C. E., & Acosta, L. P. (2024) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-61973-1_5
Leveraging Peripheral Visual Stimuli for Enhanced SSVEP-Based BCIs in Fast Calibration Scenario
He, X., Allison, B. Z., Liang, W., Chen, W., Wang, X., Cichocki, A. S., & Jin, J. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3554985
Self-citationEye Blink Based Smart Assistance System for ALS Patients Using EAR Algorithm
Arun Kumar, S., Sahana, S. S., Kumar, M. A., Chinmayi, D., Nimje, A. P., & Sohan, D. N. (2025) · International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS) · doi:10.1109/iccams65118.2025.11234028
A Novel Approach to Improve SSVEP-BCI Performance Through Neurofeedback Training
Li, M., Yao, Y., Dong, B., Wang, K., Yu, H., Xu, M., & Ming, D. (2025) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc58623.2025.11254803
Impacto da Taxa de Amostragem em Redes Neurais Convolucionais para BCIs baseadas em SSVEP
Floriano, A., Malinowski, E. L., Filho, J. D. S. P., Figueiredo, G. V. C., Silva, P. R. D. S., & Coelho, J. J. D. S. (2025) · Congresso Latino-Americano de Software Livre e Tecnologias Abertas (Latinoware) · doi:10.5753/latinoware.2025.16448
Design and Study of Interactive Systems based on Brain- Computer Interfaces and Augmented Reality
Si-Mohammed, H. (2019) · theses.fr (ABES) · doi:10.70675/cf0fab29z353fz4851z9a78z0fa1ec26ec54
Benaroch, C. (2021) · theses.fr (ABES) · doi:10.70675/c2704384z058az4affza403z92acc3ec08f8 · Cited by 1
A visual Brain-Computer Interface for gaze-free communication : Algorithms & applications
Kerchove, A. V. D. (2024) · theses.fr (ABES) · doi:10.70675/7ee5680eze506z4dbdz8078z01924f3e063a
Stability of the Default Mode Network Estimated from Electroencephalogram
Silva, J., Syrjänen, E., & Ästrand, E. (2025) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner61569.2025.11588924
Kwon, J., Han, H., Hwang, J., Nam, S., Lee, T., Cha, H., Ahn, K.-H., & Im, C. (2026) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2026.3729803
Metadata
- Authors
- Allison, B., Luth, T., Valbuena, D., Teymourian, A., Volosyak, I., & Graser, A.
- Affiliations
- Graz University of Technology (AT)
- University of Bremen (DE)
- Venue
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2010-04
- Volume
- 18
- Issue
- 2
- Pages
- 107-116
- ISSN
- 1534-4320 (ISSN-L)
- 1558-0210
- OpenAlex
- W2137237725
- Cited by
- 344
- References
- 43
- Citations by year
- 2026: 3 · 2025: 13 · 2024: 12 · 2023: 14 · 2022: 21 · 2021: 13 · 2020: 18 · 2019: 23 · 2018: 35 · 2017: 25 · 2016: 24 · 2015: 23 · 2014: 27 · 2013: 33 · 2012: 22
- FWCI
- 17.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Neural Systems and Rehabilitation Engineering (publishedVersion)
- PubMed (publishedVersion)
- PUB – Publications at Bielefeld University (Bielefeld University) (submittedVersion)
- Publikationen an der Universität Bielefeld (Universität Bielefeld) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Keywords
- brain-computer interface, steady-state visual evoked potentials, BCI usability, user demographics, age differences, gender differences, user preferences
- MeSH terms
- Adolescent, Adult, Aged, Aging, Brain, Communication, Communication Aids for Disabled, Communication Devices for People with Disabilities, Computer Literacy, Demography, Electroencephalography, Evoked Potentials, Female, Humans, Individuality, Male, Middle Aged, Photic Stimulation, Sex Characteristics, Software, User-Computer Interface, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review